Providers of vehicle insurance generally seek to determine an insurance policy premium that is appropriate given the risk of losses recognizable under the policy (e.g., damage to the policy holder's vehicle, damage to another vehicle, injury to a passenger of another vehicle, etc.). Moreover, it is well understood among insurance providers that past driving behaviors of an individual can help to predict the likelihood of a recognizable loss in the future. For example, someone who has had a large number of moving violations may be more likely to incur a recognizable loss (e.g., by causing an accident) than someone who has had no moving violations. Typically, driving behaviors such as this are learned based on driving records, and/or information provided by the insurance policy holder (or potential policy holder) in response to queries from the insurer. Generally, individuals demonstrating driving behaviors corresponding to a lower risk of loss may be assigned a more positive rating, and may therefore be offered lower premiums for a given level of coverage. Conversely, individuals demonstrating behaviors corresponding to a higher risk of loss may be assigned a more negative rating, and may therefore be offered higher premiums for the same level of coverage.
Unfortunately, insurers generally have access to a very limited amount of information with respect to driving behaviors of current or potential policy holders. Moreover, some driving behaviors that substantially affect the likelihood of losses may not be known or well characterized, and in any case may be difficult to assess based on driving records, questionnaires, or other current techniques for learning driver behaviors. As a result, insurance ratings and premiums determined for the policy holder may be poorly correlated to the policy holder's true risk of loss.